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Symmetry-Enriched Learning: A Category-Theoretic Framework for Robust
  Machine Learning Models

Symmetry-Enriched Learning: A Category-Theoretic Framework for Robust Machine Learning Models

18 September 2024
Ronald Katende
    AAML
ArXiv (abs)PDFHTML

Papers citing "Symmetry-Enriched Learning: A Category-Theoretic Framework for Robust Machine Learning Models"

4 / 4 papers shown
Title
Category Theory in Machine Learning
Category Theory in Machine Learning
Dan Shiebler
Bruno Gavranović
Paul W. Wilson
60
31
0
13 Jun 2021
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
M. Bronstein
Joan Bruna
Taco S. Cohen
Petar Velivcković
GNN
362
1,163
0
27 Apr 2021
Neural Message Passing for Quantum Chemistry
Neural Message Passing for Quantum Chemistry
Justin Gilmer
S. Schoenholz
Patrick F. Riley
Oriol Vinyals
George E. Dahl
598
7,496
0
04 Apr 2017
Group Equivariant Convolutional Networks
Group Equivariant Convolutional Networks
Taco S. Cohen
Max Welling
BDL
176
1,946
0
24 Feb 2016
1